\section{Introduction}
Many humans suffer from various sleep disorders. Often they are examined in
so-called sleep laboratories, where different sensors measure their physical
activity. This Polysomnography (PSG) is a multi-parametric test, which records
all the biophysiological changes occurring during sleep. The PSG consists of many 
records, including an electroencephalogram (EEG),
electrooculogram (EOG), electrocardiogram (ECG) and the muscle activity:
electromyogram (EMG).

The institute of medical statistics and epidemiology (IMSE) of the technical
university of Munich does a clinical study on this subject. Together with the
clinic for rehabilitation, pneumology and orthopaedics of Bad Reichenhall, they
examine the sensor data from patients with sleep disorder. Within the scope of
this study, three accelerometer are used to measure the physical activity of
such patients. Thus far, different applications had to be used to evaluate,
analyze and visualize the resulting data. To improve the processing and the
evaluation of this data, a convenient application is needed.

\subsection{Aim}
The aim of the project is the development, implementation and the testing of an
application that can be used to analyze the data from accelerometer sensors and
compare it to the data resulting from the EMGs. Due to the different types of 
accelerometers that are used in this study, the application has to support the
different data formats. The main task of the application is the evaluation,
visualization and the comparison of different sensor data.

The evaluation of the data includes the extraction of leg movements and
the detection of so-called PLMs (Periodic Limb Movement, more in section
\ref{sec:background}). Furthermore, data from three different sensors has to be
processible and comparable simultaneously, so
that the similarity and quality of the different data can be determined.

Another part of this project is the development of a mobile application,
which can be used to monitor the patients physical activity. 
To fulfill this task the application has to be capable of accessing
the accelerometer of the used mobile device, and save the data into a well-known
data format. 

The mobile application has to be tested and the data has to be compared to the
other accelerometers, so that the efficiency and usability of a mobile device as an
alternative to the other sensors can be evaluated.
\subsection{Background information}
\label{sec:background}
The Periodic limb movement disorder (PLMD) refers to a sleep disorder, which is
characterized by involuntary movements of a patients limbs during sleep. As a
consequence of those movements the patient will suffer from excessive daytime
sleepiness (EDS), resulting in a lack of energy and persistent sleepiness.

PLMD can be diagnosed by using polysomnograms (PSG), which are also used in the
study being done by IMSE. For this project the most important data from the PSG
is the muscle tension in the body. To record this tension, electroymyograms
(EMG) are used, they measure the electrical activity produced by skeletal muscles.

Other sensors measure the physical activity of the body, particularly the activity
of the legs. For that measurement GT1X or GT3X Actigraph accelerometers are
used. Those sensors are able to log movement in all three axes (GT1X
supports only one axis). The sensors can be used with different logging
intervals (1 to 60 seconds) and supports the logging of raw data (30 HZ).

By comparing the EMG data with the data from the accelerometers it can be
determined, if the accelerometers provide sufficiently accurate data for being
used in the PLMD diagnosis. 
